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Build and deploy ML systems on Instacart's Economics team, blending economic theory with machine learning to solve marketplace problems like matching, logistics, online advertising, and causal inference using Python, SQL, Pandas, scikit-learn, and XGBoost.
Staff Data Scientist leading the Fuel Detection Model, applying ML and remote sensing to satellite/environmental data to estimate vegetation structure, fuel loads, and wildfire risk for utility partners.
Lead AI/ML teams to build ad-tech algorithms (bid prediction, yield optimization, fraud detection) that maximize publisher revenue and advertiser performance using Python, TensorFlow, and real-time MLOps on cloud platforms.
Machine Learning Engineer at Cinder building classification pipelines, confidence cascading, and model training/serving infrastructure for a trust & safety platform, using Python, PyTorch, scikit-learn, XGBoost, and LLMs.
Build and scale ML-driven dispute optimization systems, including training, deploying, and monitoring models, plus real-time data pipelines and feature stores for Checkout.com’s fintech platform.
A Data Scientist II designs and deploys AI models for customer engagement, partnering with clients to integrate data pipelines and reinforcement learning systems using Python, SQL, and ML libraries.
Entry-level Data Scientist for Dec 2026/May 2027 grads at an auto-lending company, building predictive models and translating data insights into business strategies using Python, R, SQL, and ML libraries like XGBoost and scikit-learn.
Middle Data Scientist builds ML models for personalized loan pricing at a major Russian bank, using Python, SQL, and reinforcement learning to optimize financial metrics like revenue and margin.
We are looking for a Middle/Senior Data Scientist to join the Data Science team of a leading financial institution in Ukraine. We are open to considering candidates at the Middle to Senior level, depending on their…
Data Scientist builds ML models to assess credit, market, and fraud risks for a major Ukrainian bank, using Python, SQL, and cloud tools like SageMaker.
The Forward-Deployed Data Scientist designs and builds end-to-end machine learning solutions for clients, managing the full ML pipeline from data transformation to model deployment. This role involves direct customer collaboration to drive business value and partnering with product teams to advance reinforcement learning algorithms.
Senior MLOps Engineer in Singapore builds and maintains AWS-based pipelines to deploy, scale, and monitor machine learning models for manufacturing and semiconductor analytics, focusing on GenAI and classical ML workflows.
Build and deploy data models to analyze credit card portfolios, customer behavior, and transaction trends, then translate insights into actionable strategies for Kotak Mahindra Bank’s financial services.
The Applied AI ML Associate develops and manages fraud and credit risk models for JPMorgan Chase's digital bank. The role involves end-to-end model lifecycle management, performance monitoring, and regulatory compliance using Python and machine learning frameworks.
Staff Data Scientist leading homeowners insurance pricing and risk modeling at Porch Group, building and deploying GLM and ML models (Python, SQL, BigQuery/GCP) for underwriting, profitability, and retention.
Develops AI/ML solutions (predictive models, generative AI, agentic systems) for government case management modernization, focusing on compliance, MLOps, and data-driven decision tools.
The Senior AI Engineer will build and maintain generative AI agents and classical ML models in production using Azure AI Foundry and Python. This role focuses on executing technical specifications, implementing LLMOps frameworks, and ensuring system observability within a global team.
Design, build, and deploy ML models for forecasting, supply-chain optimization, and anomaly detection using Python and SQL, then communicate insights via dashboards.
Design and operate large-scale machine learning systems to detect and prevent fraud, abuse, and risk across Block’s financial products using Python, TensorFlow, and real-time decisioning pipelines.
Lead large-scale data science initiatives for a real-estate platform, defining strategies, mentoring teams, and deploying ML models to solve ambiguous business problems.
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